Deep Learning Solutions

Deep Learning is the fastest-growing field in machine learning. Using the development of complex, multi-layered non-linear algorithms based on Deep Neural Networks (DNNs). The software learns, in a very real sense, to recognize patterns in digital representations of sounds, images, and other data, helping to solve many big data problems such as computer vision, speech recognition, and natural language processing. Practical examples include:

GPUs have provided ground-breaking performance to accelerate deep learning research with thousands of computational cores and up to 100x application throughout when compared to CPUs alone. NVIDIA GPU technology has given the abilty to learn at a speed, accuracy, and scale that are driving true artificial intelligence.

Accelerated computing has revolutionised abroad range of industries with over four hundred applications optimised for GPUs to help you accelerate your work. Download the full list here.

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Unsure what you need? Got technical questions? Our team are here to help you through the whole process, from design to delivery.

Fully customisable

We customise all of our systems to match your budgetary needs and performance requirements. We don't do 'one size fits all'.

Tried & trusted

We've been in business since 1987 and are trusted by some of the leading names in the Aviation, Defence and Marine industries.

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The systems listed on this page are just a small selection of what we can offer. So if you’re looking for something in particular, Contact us and we'll help you design a custom solution to meet your needs.

Our expertise

How we work

We are an open-architecture manufacturer and have close partnerships with industry leading software and hardware vendors. All of our solutions are designed with scalability, longevity and the lowest total cost of ownership in mind. We do not use any proprietary hardware.

Projects

Centre for Cognitive Ageing

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Conventional ADAS technology can detect some objects, do basic classification, alert the driver of hazardous road conditions, and in some cases, slow or stop the vehicle. This level of ADAS is great for applications like blind spot monitoring, lane change assistance, and forward collision warnings.

With NVIDIA self-driving car solutions, a vehicle's ADAS can discern a police car from a taxi; an ambulance from a delivery truck; or a parked car from one that is about to pull out into traffic. It can even extend this capability to identify everything from cyclists on the pavement to absent-minded pedestrians.

Image recognition refers to a DNN's ability to identify images and objects within that image, including faces. This technology can be used for shape identification for modeling purposes, social media photo tagging, optical character recognition, and more.

Voice recognition is a rapidly developing branch of deep learning as there are numerous applications for this technology. Language translation word by word in itself isn't complicated, but often the meaning of a word or phrase is lost with simple word to word translation. Fortunately, Deep learning is ideal for processing big, complicated data sets, allowing for a more natural translation that can detect the nuances of speech and the meaning and context of a word or phrase. An example of this would be Google's Neural Machine Translation System.

Deep learning lets you uncover patterns in large data sets to reveal new knowledge and insights in hours or minutes. This results in powerful applications for deep learning such as risk and threat analysis, business analytics, and medical diagnosis

Life Sciences applications, such as Bioinformatics, Molecular Dynamics, and Quantum Chemistry are helped greatly by the massive parallel architecture of NVIDIA's GPUs.

Tesla® GPUs provide bio-physicists and computational chemists with the tools to push the boundaries of bio-chemical research, optimizing the scientific workflow and accelerating the pace of research.